code: def run_sample_decode(
      infer_model,
      infer_sess,
      model_dir,
      hparams,
      summary_writer,
      src_data,
      tgt_data,
  ):
      """Sample decode a random sentence from src_data."""
      with infer_model.graph.as_default():
          (
              loaded_infer_model,
              global_step,
          ) = model_helper.create_or_load_model(
              infer_model.model, model_dir, infer_sess, "infer"
          )
  
      _sample_decode(
          loaded_infer_model,
          global_step,
          infer_sess,
          hparams,
          infer_model.iterator,
          src_data,
          tgt_data,
          infer_model.src_placeholder,
          infer_model.batch_size_placeholder,
          summary_writer,
      )
  
imports: from __future__ import print_function
  import math
  import os
  import random
  import time
  import tensorflow
  from .None import inference, gnmt_model
  from .gnmt import attention_model, model
  from .gnmt import model_helper
  from .gnmt.utils import nmt_utils, misc_utils
label_desc: Use image node_id 1 for calling a global function with example usage: run_sample_decode(infer_model, infer_sess, model_dir, hparams, summary_writer, src_data, tgt_data) without return types